Mapping and Localization, Map for Autonomous Vehicles

Vehicle self-localization is an important and challenging issue in current driving assistance and autonomous driving research activities. Mainly two kinds of methods for vehicle self-localization: active sensor based and passive sensor based. Active sensor based localization was firstly proposed for robot localization, and was introduced into autonomous driving recently. The Simultaneous Localization and Mapping (SLAM) techniques are the representative in active sensor based localization. The passive sensor based localization technologies are categorized and explained based on the type of sensors, Global Navigation Satellite System (GNSS), inertial sensors and cameras. Finally, our challenges on self-localization in urban canyon by the system integration of passive sensors are introduced. GNSS error has been improved for the purpose of the self-localization in urban canyon. The performance of the proposed method would suggest possible solution autonomous vehicles which makes use of passive sensors more.

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